Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

HLA class II sequence variants influence tuberculosis risk in populations of European ancestry


Mycobacterium tuberculosis infections cause 9 million new tuberculosis cases and 1.5 million deaths annually1. To identify variants conferring risk of tuberculosis, we tested 28.3 million variants identified through whole-genome sequencing of 2,636 Icelanders for association with tuberculosis (8,162 cases and 277,643 controls), pulmonary tuberculosis (PTB) and M. tuberculosis infection. We found association of three variants in the region harboring genes encoding the class II human leukocyte antigens (HLAs): rs557011[T] (minor allele frequency (MAF) = 40.2%), associated with M. tuberculosis infection (odds ratio (OR) = 1.14, P = 3.1 × 10−13) and PTB (OR = 1.25, P = 5.8 × 10−12), and rs9271378[G] (MAF = 32.5%), associated with PTB (OR = 0.78, P = 2.5 × 10−12)—both located between HLA-DQA1 and HLA-DRB1—and a missense variant encoding p.Ala210Thr in HLA-DQA1 (MAF = 19.1%, rs9272785), associated with M. tuberculosis infection (P = 9.3 × 10−9, OR = 1.14). We replicated association of these variants with PTB in samples of European ancestry from Russia and Croatia (P < 5.9 × 10−4). These findings show that the HLA class II region contributes to genetic risk of tuberculosis, possibly through reduced presentation of protective M. tuberculosis antigens to T cells.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Figure 1: Regional association plot of the HLA 6p21 locus for PTB (n = 3,686), all TB (n = 8,162) and M. tuberculosis infection with or without TB (n = 14,723).

Accession codes


Gene Expression Omnibus


  1. World Health Organization. WHO Global Tuberculosis Report 2014, WHO/HTM/TB/2014.08 (World Health Organization, 2014).

  2. Fox, G.J. & Menzies, D. Epidemiology of tuberculosis immunology. Adv. Exp. Med. Biol. 783, 1–32 (2013).

    Article  CAS  Google Scholar 

  3. Comstock, G.W. Tuberculosis in twins: a re-analysis of the Prophit survey. Am. Rev. Respir. Dis. 117, 621–624 (1978).

    CAS  PubMed  Google Scholar 

  4. Sigurdsson, S. Tuberculosis in Iceland. 1976. Laeknabladid 91, 69–102 (2005).

    PubMed  Google Scholar 

  5. Sigurdsson, S. Um berklaveiki á Íslandi. Laeknabladid 62, 3–50 (1976).

    Google Scholar 

  6. Bothamley, G.H., Ditiu, L., Migliori, G.B. & Lange, C. Active case finding of tuberculosis in Europe: a Tuberculosis Network European Trials Group (TBNET) survey. Eur. Respir. J. 32, 1023–1030 (2008).

    Article  CAS  Google Scholar 

  7. Gudbjartsson, D.F. et al. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet. 47, 435–444 (2015).

    Article  CAS  Google Scholar 

  8. DePristo, M.A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Article  CAS  Google Scholar 

  9. Cobat, A. et al. Two loci control tuberculin skin test reactivity in an area hyperendemic for tuberculosis. J. Exp. Med. 206, 2583–2591 (2009).

    Article  CAS  Google Scholar 

  10. Cobat, A. et al. Tuberculin skin test negativity is under tight genetic control of chromosomal region 11p14-15 in settings with different tuberculosis endemicities. J. Infect. Dis. 211, 317–321 (2015).

    Article  CAS  Google Scholar 

  11. Emilsson, V. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).

    Article  CAS  Google Scholar 

  12. Curtis, J. et al. Susceptibility to tuberculosis is associated with variants in the ASAP1 gene encoding a regulator of dendritic cell migration. Nat. Genet. 47, 523–527 (2015).

    Article  CAS  Google Scholar 

  13. Thye, T. et al. Common variants at 11p13 are associated with susceptibility to tuberculosis. Nat. Genet. 44, 257–259 (2012).

    Article  CAS  Google Scholar 

  14. Thye, T. et al. Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2. Nat. Genet. 42, 739–741 (2010).

    Article  CAS  Google Scholar 

  15. Chimusa, E.R. et al. Genome-wide association study of ancestry-specific TB risk in the South African Coloured population. Hum. Mol. Genet. 23, 796–809 (2014).

    Article  CAS  Google Scholar 

  16. Sollid, L.M. Coeliac disease: dissecting a complex inflammatory disorder. Nat. Rev. Immunol. 2, 647–655 (2002).

    Article  CAS  Google Scholar 

  17. Sollid, L.M., Qiao, S.W., Anderson, R.P., Gianfrani, C. & Koning, F. Nomenclature and listing of celiac disease relevant gluten T-cell epitopes restricted by HLA-DQ molecules. Immunogenetics 64, 455–460 (2012).

    Article  Google Scholar 

  18. Lundin, K.E.A., Scott, H., Fausa, O., Thorsby, E. & Sollid, L.M. T cells from the small intestinal mucosa of a DR4, DQ7/DR4, DQ8 celiac disease patient preferentially recognize gliadin when presented by DQ8. Hum. Immunol. 41, 285–291 (1994).

    Article  CAS  Google Scholar 

  19. Aly, T.A. et al. Extreme genetic risk for type 1A diabetes. Proc. Natl. Acad. Sci. USA 103, 14074–14079 (2006).

    Article  CAS  Google Scholar 

  20. Zanelli, E., Breedveld, F.C. & de Vries, R.R. HLA class II association with rheumatoid arthritis: facts and interpretations. Hum. Immunol. 61, 1254–1261 (2000).

    Article  CAS  Google Scholar 

  21. Rider, L.G. The heterogeneity of juvenile myositis. Autoimmun. Rev. 6, 241–247 (2007).

    Article  CAS  Google Scholar 

  22. Lindestam Arlehamn, C.S., Lewinsohn, D., Sette, A. & Lewinsohn, D. Antigens for CD4 and CD8 T cells in tuberculosis. Cold Spring Harb. Perspect. Med. 4, a018465 (2014).

    Article  Google Scholar 

  23. Lindestam Arlehamn, C.S. & Sette, A. Definition of CD4 immunosignatures associated with MTB. Front. Immunol. 5, 124 (2014).

    Article  Google Scholar 

  24. Arlehamn, C.S. et al. Dissecting mechanisms of immunodominance to the common tuberculosis antigens ESAT-6, CFP10, Rv2031c (hspX), Rv2654c (TB7.7), and Rv1038c (EsxJ). J. Immunol. 188, 5020–5031 (2012).

    Article  Google Scholar 

  25. Miyadera, H., Ohashi, J., Lernmark, Å., Kitamura, T. & Tokunaga, K. Cell-surface MHC density profiling reveals instability of autoimmunity-associated HLA. J. Clin. Invest. 125, 275–291 (2015).

    Article  Google Scholar 

  26. Busch, R. et al. On the perils of poor editing: regulation of peptide loading by HLA-DQ and H2-A molecules associated with celiac disease and type 1 diabetes. Expert Rev. Mol. Med. 14, e15 (2012).

    Article  Google Scholar 

  27. Tollefsen, S. et al. Structural and functional studies of trans-encoded HLA-DQ2.3 (DQA1*03:01/DQB1*02:01) protein molecule. J. Biol. Chem. 287, 13611–13619 (2012).

    Article  CAS  Google Scholar 

  28. Yin, L., Maben, Z.J., Becerra, A. & Stern, L.J. Evaluating the role of HLA-DM in MHC class II–peptide association reactions. J. Immunol. 195, 706–716 (2015).

    Article  CAS  Google Scholar 

  29. Cho, K.J., Walseng, E., Ishido, S. & Roche, P.A. Ubiquitination by March-I prevents MHC class II recycling and promotes MHC class II turnover in antigen-presenting cells. Proc. Natl. Acad. Sci. USA 112, 10449–10454 (2015).

    Article  CAS  Google Scholar 

  30. Chadwick, L.H. The NIH Roadmap Epigenomics Program data resource. Epigenomics 4, 317–324 (2012).

    Article  CAS  Google Scholar 

  31. Sheffield, N.C. et al. Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions. Genome Res. 23, 777–788 (2013).

    Article  CAS  Google Scholar 

  32. Chapman, S.J. & Hill, A.V. Human genetic susceptibility to infectious disease. Nat. Rev. Genet. 13, 175–188 (2012).

    Article  CAS  Google Scholar 

  33. Fernando, M.M. et al. Defining the role of the MHC in autoimmunity: a review and pooled analysis. PLoS Genet. 4, e1000024 (2008).

    Article  Google Scholar 

  34. de Bakker, P.I. et al. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat. Genet. 38, 1166–1172 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Meyer, C.G. & Thye, T. Host genetic studies in adult pulmonary tuberculosis. Semin. Immunol. 26, 445–453 (2014).

    Article  CAS  Google Scholar 

  36. Etokebe, G.E. et al. Toll-like receptor 2 (P631H) mutant impairs membrane internalization and is a dominant negative allele. Scand. J. Immunol. 71, 369–381 (2010).

    Article  CAS  Google Scholar 

  37. Knezević, J. et al. Heterozygous carriage of a dysfunctional Toll-like receptor 9 allele affects CpG oligonucleotide responses in B cells. J. Biol. Chem. 287, 24544–24553 (2012).

    Article  Google Scholar 

  38. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  Google Scholar 

  39. Styrkarsdottir, U. et al. Nonsense mutation in the LGR4 gene is associated with several human diseases and other traits. Nature 497, 517–520 (2013).

    Article  CAS  Google Scholar 

  40. Kutyavin, I.V. et al. A novel endonuclease IV post-PCR genotyping system. Nucleic Acids Res. 34, e128 (2006).

    Article  Google Scholar 

  41. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    Article  CAS  Google Scholar 

  42. Price, A.L. et al. The impact of divergence time on the nature of population structure: an example from Iceland. PLoS Genet. 5, e1000505 (2009).

    Article  Google Scholar 

  43. Kent, W.J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).

    Article  CAS  Google Scholar 

  44. McLaren, W. et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26, 2069–2070 (2010).

    Article  CAS  Google Scholar 

  45. Pruitt, K.D., Tatusova, T., Brown, G.R. & Maglott, D.R. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Res. 40, D130–D135 (2012).

    Article  CAS  Google Scholar 

  46. Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

    Article  CAS  Google Scholar 

  47. Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65–70 (1979).

    Google Scholar 

  48. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  49. Davydov, E.V. et al. Identifying a high fraction of the human genome to be under selective constraint using GERP. PLoS Comput. Biol. 6, e1001025 (2010).

    Article  Google Scholar 

  50. Garber, M. et al. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 25, i54–i62 (2009).

    Article  CAS  Google Scholar 

  51. Wang, J. et al. Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome Res. 22, 1798–1812 (2012).

    Article  CAS  Google Scholar 

  52. Ward, L.D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930–D934 (2012).

    Article  CAS  Google Scholar 

Download references


The authors thank the study participants and the staff at the Patient Recruitment Center and the deCODE genetics core facilities. We thank S. Balen (University of Rijeka) and M. Balija (Croatian Institute for Transfusion Medicine) for assistance in the collection of blood samples, S. Grle-Popovic for assistance in collection of blood samples of tuberculosis patients treated at the University Hospital Center, Zagreb, and J. Pavelic (Ruđer Bošković Institute) for providing resources and advice. This work was supported by the US National Institute of Allergy and Infectious Diseases grant HHSN266200400064C (deCODE Genetics, A. Kong, K.G.K., M.G., M.K.), UK Wellcome Trust grants 088838/Z/09/Z and 095198/Z/10/Z (S.N.), EU Framework Programme 7 Collaborative grant 201483 (University of Cambridge and S.N.), European Research Council Starting grant 260477 and Royal Society grants UF0763346 and RG090638 (S.N.). S.N. is also supported by a Wellcome Trust Senior Research fellowship and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre.

Author information

Authors and Affiliations



G.S., D.F.G., B.V.H., A. Kong, U.T., T.B., I.J. and K.S. designed the study and interpreted the results. T.B., K.G.K., M.G., L.J.G., A.L., M.K. and K.B. coordinated and managed phenotype data ascertainment and Icelandic subject recruitment. S.N., J.C.B. and Y.L. coordinated, managed, genotyped and analyzed the Russian cohort sample set. L.B.K., J.K. and Z.D. coordinated and managed the Croatian cohort phenotypes and samples, which were genotyped and analyzed by deCODE. G.S., H.T.H., G.M., S.A.G., O.T.M., U.T. and I.J. performed the sequencing, genotyping and expression analyses. G.S., D.F.G., B.V.H., S.A.G., A.G., Adalbjorg Jonasdottir, Aslaug Jonasdottir, A. Karason, H.K. and I.J. performed HLA typing and analysis of HLA data. G.S., D.F.G., B.V.H., A.G., S.A.G., P.S., A. Kong, G.M. and I.J. performed the statistical and bioinformatics analyses. G.S., D.F.G., S.N., I.J. and K.S. drafted the manuscript. All authors contributed to the final version of the manuscript.

Corresponding authors

Correspondence to Ingileif Jonsdottir or Kari Stefansson.

Ethics declarations

Competing interests

G.S., D.F.G., B.V.H., L.J.G., A.G., S.A.G., H.T.H., Adalbjorg Jonasdottir, Aslaug Jonasdottir, A. Karason, H.K., O.T.M., P.S., A. Kong, G.M., U.T., I.J. and K.S. are employed by deCODE Genetics/Amgen, Inc.

Integrated supplementary information

Supplementary Figure 1 Q-Q plots of tuberculosis GWAS results.

Q-Q plots using uncorrected (red) and corrected (blue, using the method of genomic control) χ2 statistics from the tuberculosis GWAS of pulmonary tuberculosis, all tuberculosis and M. tuberculosis. All P-values below 0.05 are plotted.

Supplementary Figure 2 Principal components plot of cases and controls.

The figure shows first two principal components of the Icelandic cases and controls used in the association. Pulmonary tuberculosis, all tuberculosis and M. tuberculosis infected cases are plotted in blue, and population controls in black.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–2, Supplementary Tables 1–6 and 8–12, and Supplementary Note (PDF 1644 kb)

Supplementary Table 7

Association signals of imputed classical HLA alleles with PTB in Iceland. HLA alleles at four digit levels were established using imputation of sequence data from a set of 2,614 whole-genome sequenced individuals (XLSX 38 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sveinbjornsson, G., Gudbjartsson, D., Halldorsson, B. et al. HLA class II sequence variants influence tuberculosis risk in populations of European ancestry. Nat Genet 48, 318–322 (2016).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing